A comparison of local and aggregated climate model outputs with observed data

Abstract

A comparison of local and aggregated climate model outputs with observed data. Hydrol. Sci. J. 55 (7), 1094-1110.Abstract We compare the output of various climate models to temperature and precipitation observations at 55 points around the globe. We also spatially aggregate model output and observations over the contiguous USA using data from 70 stations, and we perform comparison at several temporal scales, including a climatic (30-year) scale. Besides confirming the findings of a previous assessment study that model projections at point scale are poor, results show that the spatially integrated projections are also poor. Comparaison de sorties locales et agrégées de modèles climatiques avec des données observéesRésumé Nous comparons les résultats de plusieurs modèles climatiques avec les observations de température et de précipitation en 55 points du globe. De plus, nous agrégeons spatialement les sorties de modèles et les observations couvrant les Etats-Unis d'Amérique à partir des données de 70 stations, et nous procédons à une comparaison à plusieurs échelles temporelles, y compris à l'échelle climatique (30 ans). Les résultats sont non seulement cohérents avec ceux d'une évaluation antérieure pour conclure que les projections par modélisation à l'échelle ponctuelle sont pauvres, mais montrent aussi que les projections intégrées dans l'espace sont également pauvres.

Broad-scale ecosystem services of European wetlands—overview of the current situation and future perspectives under different climate and water management scenarios

“…The WaterGAP model provides a scientifically-sound basis for future hydrological predictions when coupled with stakeholder-based scenarios. We are mindful of the uncertainties of using the GCM results (Anagnostopoulos et al 2010) as well as downscaling of the GCM scenarios to hydrological models (Kundzewicz and Stakhiv 2010), and of the importance of other variables in determining wetlands' character and ultimately the services they provide, including temperature, geology and lithology, and management practices. It means that future case studies for different hydrological, morphological and ecological settings are required to understand the underlying mechanisms and develop mitigation strategies.…”

Effect of modelling scale on the assessment of climate change impact on river runoff

“…This step of pre-processing, often referred to as "downscaling", is essential due to the fact that the GCMs remain coarse in spatial resolution and are unable to resolve several sub-grid scale features (Grotch and MacCracken 1991) such as topography, clouds and land use (Fowler et al 2007). Anagnostopoulos et al (2010) showed that GCMs, on their own, cannot accurately reconstruct the past even at sub-continental to continental scales, and perform poorly at regional scales. This is one of the reasons why Kundzewicz and Stakhiv (2010) concluded that climate models are not yet "ready for prime time" in water resources management applications.…”

Are climate models “ready for prime time” in water resources management applications, or is more research needed?

“…Anagnostopoulos et al (2010) show that climate models, on their own, cannot accurately reconstruct the past even at sub-continental to continental scales, and perform poorly at regional scales. Comparison of model performance with station (data-based cell vs model-based cell) data is relatively poor, being somewhat better for temperature, and worse for precipitation.…”

“…The paper by Anagnostopoulos et al (2010) and the opinion paper by Wilby (2010) tackle the utility and accuracy of information generated by climate models and its use in water resources applications. Anagnostopoulos et al (2010) show that climate models, on their own, cannot accurately reconstruct the past even at sub-continental to continental scales, and perform poorly at regional scales.…”